Spring 2019 Course Offerings

Course Title Description Credit Instructor CRN When Where
GS 19501 Preparing for Your Undergraduate Research Experience This course is for prospective Purdue undergraduate researchers who are interested in conducting undergraduate research or creative endeavors. Purdue students who have not already started an independent research project with a research mentor will learn valuable skills to market themselves to individuals and research programs. Throughout the course, students will develop components for a final application packet to submit to a research team or program they choose. 1 JJ Sadler, Amy Childress 23139 Online Online
GS 29501 Understanding Your Undergraudate Research Experience I This course is for current Purdue undergraduate researchers to hone skills necessary for successfully reflecting on and completing the experience. During this course, students will utilize their research experience to apply skills such as managing time with a research project, communicating your research, utilizing Purdue Libraries' resources, and providing feedback to peer researchers. Students will deliver and critique research elevator pitches about their own project. 1 JJ Sadler, Amy Childress 23138 Online Online
GS 39501 Understanding Your Undergraudate Research Experience II This course is for current Purdue undergraduate researchers to build upon the previous course and focus on research data collection, analysis, and communication for current Purdue undergraduate researchers. During this course, students will learn and discuss various forms of data and collection practices. Students will develop their own academic poster to present their research project's data and implications. 1 JJ Sadler, Amy Childress 23140 Online Online
ILS 29500 Data Science and Society: Ethical, Legal, Social Issues This course provides an introduction to Ethical, Legal, Social Issues (ELSI) in Data Science. Students will be introduced to interdisciplinary theoretical and practical frameworks that can aid in exploring the impact and role of Data Science in society. Simultaneous or previous enrollment in CS 24200 Introduction to Data Science or equivalent is a suggested prerequisite. This is a writing-intensive course. Students will work individually and on collaborative assignments. 1.0 Kendall Roark 20568 T, 1:30-2:20 KRAN 250
ILS 29500 Foundations of the Data Mind: An Interlocking Modules Approach: Introduction to Data Management This course is offered as part of three one-credit courses that combine to meet a set of core competencies in data science. The courses, offered through three colleges (Philosophy, Purdue Libraries, and Electrical Engineering), cover principles of data management and organization, data analysis and visualization, and ethical and social implications of data science, providing a strong foundation for subsequent coursework. ILS 295 provides a foundation in the concepts of data organization, management, preservation, and publication. Students will develop an ability to locate, access, transform, and evaluate data to answer research questions. They will communicate the results of their data searches, and format the data for sharing. 1.0 Sarah Huber, Wei Zakharov 19868 W, 1:30-2:20 BRNG 1268
ILS 49000 Special Topics in Information and Data Science Intensive study on specific topics in information or data science that are not otherwise covered by courses currently offered at Purdue. Students will 1) Critically examine and apply information and data sciences to various disciplines; 2) Develop practical skills and apply them to their disciplinary research. Plan of study and assessment is agreed upon by faculty and student before registration. 1.0-3.0 Clarence Maybee 21216 Arr Hrs  
ILS 59500 Creating Informed Learners: Information Literacy Assignments for the Disciplinary Classroom This course will introduce you to theories and practices for developing information literacy assignments for use in a disciplinary classroom. You will learn about the components of informed learning design, a design model for creating assignments that enable students to learn to use information as they learn course content. Across the semester, you will complete assignments in which you apply the components of informed learning design to develop course curricula in which students intentionally use information to learn in a discipline-focused classroom. The course does not require prerequisites. 1.0 Clarence Maybee 19608 MW, 6:30-7:20 KRAN 202
ILS 59500 Data Management and Curation for Qualitative Researchers This course offers an interdisciplinary introduction to data management and curation with a focus on the use, value, and organization of data, materials, infrastructure, tools, and scholarly communication in qualitative research. The course will introduce literature concerning ethical and legal considerations of data management and curation, and will provide opportunity for hands-on digital, data literacy, and data manipulation skills development. 3.0 Kendall Roark 19627 T, 4:30-7:20 WALC 3045
ILS 59500 Data Management at the Bench Intensive study of selected topics varying from semester to semester, from the practice of information and data sciences. Topics may include data management and organization, digital scholarship, data visualization, computer languages for data and information science, information literacy, archival literacy, and emerging trends in information and data science. Permission of the instructor is required for undergraduates. 2.0 Megan Sapp Nelson, Chao Cai 19600 T, 11:30-12:20 WALC 3045
Pete Pascuzzi, Chao Cai 19588 R, 1:30-3:20 WALC 3045
ILS 59500 Information Strategies for Science, Technology, and Engineering Research This course focuses on information strategies for successful research in science, engineering, and technology disciplines. Students will learn about how scholarly information and discipline-relevant grey literature (e.g. patents, technical standards) are created, organized, disseminated, retrieved, and managed. In addition, students will learn strategies to critically evaluate information and present their research effectively and ethically. 1.0 Margaret Phillips, David Zwicky 19574 DIS  
ILS 59500 Introduction to Systematic Review for Health Sciences Disciplines This course will introduce systematic review methodology of published health sciences literature. Students will learn to form research questions, develop inclusion and exclusion criteria, search for evidence, manage data, and assess the risk of bias. 1.0 Bethany McGowan, Jason Reed, Jane Yatcilla 19619 MW, 12:30-1:20 WALC 3045
ILS 69500 Graduate Capstone Experience in Research Data Management: Data Sharing and Publication This course walks students through the process of preparing a dataset for sharing with both internal and external audiences. Students wil select authoritative datasets for sharing and publication, apply metadata to those datasets, create documentation for end-users of the datasets, and publish the datasets to internal or external data repositories or storage as appropriate. 3.0 Megan Sapp Nelson (LEC) 19624 M, 8:30-9:20 WALC 3049
Ningning Kong (LAB) 19623 M, 9:30-11:20 WALC 3045
ILS 69500 Digital and Analog Archives An overview of archival theory and practice, including archival preservation, research, and creation of digital archives. This course will prepare students from any discipline for archival research, and will provide experience in using digital humanities tools for archival work. 3.0 Sammie Morris 19626 W, 9:30-12:20 STEW 462
ILS 69500 Introducing Digital Humanities This course will provide a sweeping introduction to many of the tools and concepts central to the Digital Humanities. DH is a newer area of study, supplementing the study and teaching of the humanities and social sciences with computing tools that provoke new questions. The course is divided into two concurrent tracks: 1) One session per week will be spent discussing readings about the central debates within the field in discussion-based lecture periods and exploring existing DH projects to gain familiarity with contemporary work; 2) Students will also learn to apply software tools to their home disciplines in weekly lab sessions where students will be required to reconceptualize their research into datasets with an eye toward building an original digital project or exhibit. There are no pre-requisites, and graduate students and advanced undergraduates are welcome from any department. While there are no technical skills required, students should know the basics of their chosen computer interface as we will be downloading software and navigating file paths. 3.0 Matthew Hannah (LEC) 19620 T, 12:00-1:15 WALC 3049
Matthew Hannah (LAB) 19621 R, 12:00-1:15 WALC 3045